A modular tool to aggregate results from bioinformatics analyses across many samples into a single report.
/lustre1/home/mass/eskalon/Porites/analysis/trimming/sortmerna/output/logs
General Statistics
| Sample Name | rRNA |
|---|---|
| 4-MF10-4a_trim_2P | 58.4% |
| 23-MF10-1a_trim_2P | 31.9% |
| 25-CC40-2b_trim_2P | 3.1% |
| 27-MF40-2b_trim_2P | 54.5% |
| 28-CC10-9b_trim_2P | 57.0% |
| 31-MF40-5b_trim_2P | 83.6% |
| 32-CC10-1b_trim_2P | 86.6% |
| 35-MF40-1b_trim_2P | 45.4% |
| 37-CC40-8b_trim_2P | 71.0% |
| 42-MF10-10b_trim_2P | 21.1% |
| 48-CC10-6b_trim_2P | 86.7% |
| 49-CC40-1b_trim_2P | 62.3% |
| 63-MF-SS-60_trim_2P | 19.2% |
| 66-MF-DS-52_trim_2P | 79.4% |
| 73-CC-SS-38_trim_2P | 79.4% |
| 75-CC-DD-84_trim_2P | 20.9% |
| 78-MF-DS-54_trim_2P | 62.4% |
| 80-1-CC-DS-86_trim_2P | 2.2% |
| 81-CC-DS-87_trim_2P | 51.8% |
| 84-CC-DD-80_trim_2P | 71.8% |
| 91-CC-DS-89_trim_2P | 87.1% |
| 94-CC-SS-37_trim_2P | 73.5% |
| 97-MF-SS-64_trim_2P | 40.3% |
| 98-MF-SS-69_trim_2P | 64.1% |
| 99-MF-SD-43_trim_2P | 2.0% |
| 100-CC-SD-73_trim_2P | 42.2% |
| 102-CC-DD-82_trim_2P | 38.1% |
| 108-CC-DD-94_trim_2P | 67.9% |
| 114-MF-SD-45_trim_2P | 14.0% |
| 117-MF-SD-44_trim_2P | 4.6% |
| 123-CC-DD-81_trim_2P | 3.1% |
SortMeRNA
Program for filtering, mapping and OTU-picking NGS reads in metatranscriptomic and metagenomic data.URL: http://bioinfo.lifl.fr/RNA/sortmernaDOI: 10.1093/bioinformatics/bts611
The core algorithm is based on approximate seeds and allows for fast and sensitive analyses of nucleotide sequences. The main application of SortMeRNA is filtering ribosomal RNA from metatranscriptomic data.